Joshua A. Rackers

1.8k total citations · 1 hit paper
16 papers, 885 citations indexed

About

Joshua A. Rackers is a scholar working on Molecular Biology, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Joshua A. Rackers has authored 16 papers receiving a total of 885 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 9 papers in Materials Chemistry and 8 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Joshua A. Rackers's work include Protein Structure and Dynamics (7 papers), Advanced Chemical Physics Studies (6 papers) and Spectroscopy and Quantum Chemical Studies (5 papers). Joshua A. Rackers is often cited by papers focused on Protein Structure and Dynamics (7 papers), Advanced Chemical Physics Studies (6 papers) and Spectroscopy and Quantum Chemical Studies (5 papers). Joshua A. Rackers collaborates with scholars based in United States, France and Finland. Joshua A. Rackers's co-authors include Jay W. Ponder, Pengyu Ren, Jean‐Philip Piquemal, Louis Lagardère, Michael J. Schnieders, Marie L. Laury, Zhi Wang, Chao Lü, Qiantao Wang and Chengwen Liu and has published in prestigious journals such as The Journal of Chemical Physics, PLoS ONE and The Journal of Physical Chemistry B.

In The Last Decade

Joshua A. Rackers

15 papers receiving 878 citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Tinker 8: Software Tools for Molecular Design

2018 488 citations Joshua A. Rackers, Zhi Wang et al. Journal of Chemical Theory and Computation profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Joshua A. Rackers United States	11	366	353	269	149	132	16	885
Jiajing Zhang China	7	337 0.9×	455 1.3×	210 0.8×	110 0.7×	134 1.0×	16	819
Omar Demerdash United States	19	296 0.8×	440 1.2×	256 1.0×	98 0.7×	103 0.8×	30	1.0k
Casper Steinmann Denmark	17	377 1.0×	246 0.7×	162 0.6×	133 0.9×	231 1.8×	36	728
Rui Qi United States	17	315 0.9×	490 1.4×	258 1.0×	84 0.6×	131 1.0×	32	1.1k
Uriel N. Morzan Argentina	15	256 0.7×	363 1.0×	148 0.6×	97 0.7×	85 0.6×	29	830
David N. LeBard United States	20	344 0.9×	680 1.9×	198 0.7×	216 1.4×	108 0.8×	25	1.1k
Zhifeng Jing United States	15	361 1.0×	630 1.8×	590 2.2×	93 0.6×	187 1.4×	26	1.5k
Lea Thøgersen Denmark	18	357 1.0×	516 1.5×	136 0.5×	71 0.5×	179 1.4×	23	1.0k
Shirin Faraji Netherlands	20	439 1.2×	189 0.5×	253 0.9×	199 1.3×	141 1.1×	68	930
Aaron M. Virshup United States	11	607 1.7×	296 0.8×	384 1.4×	255 1.7×	132 1.0×	11	1.2k

Countries citing papers authored by Joshua A. Rackers

Since Specialization

Citations

This map shows the geographic impact of Joshua A. Rackers's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Joshua A. Rackers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joshua A. Rackers more than expected).

Fields of papers citing papers by Joshua A. Rackers

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joshua A. Rackers. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Joshua A. Rackers. The network helps show where Joshua A. Rackers may publish in the future.

Co-authorship network of co-authors of Joshua A. Rackers

This figure shows the co-authorship network connecting the top 25 collaborators of Joshua A. Rackers. A scholar is included among the top collaborators of Joshua A. Rackers based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Joshua A. Rackers. Joshua A. Rackers is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

Wang, Yuanqing, Michael S. Chen, Marcus Wieder, et al.. (2025). On the design space between molecular mechanics and machine learning force fields. Applied Physics Reviews. 12(2). 10 indexed citations

Rackers, Joshua A., et al.. (2025). Strain Problems Got You in a Twist? Try StrainRelief: A Quantum-Accurate Tool for Ligand Strain Calculations. Journal of Chemical Information and Modeling. 65(13). 6613–6620.

Rackers, Joshua A., et al.. (2024). Building an ab initio solvated DNA model using Euclidean neural networks. PLoS ONE. 19(2). e0297502–e0297502. 2 indexed citations

Rackers, Joshua A., et al.. (2023). A recipe for cracking the quantum scaling limit with machine learned electron densities. Machine Learning Science and Technology. 4(1). 15027–15027. 23 indexed citations

Ema, I., et al.. (2022). Accurate Hellmann–Feynman forces from density functional calculations with augmented Gaussian basis sets. The Journal of Chemical Physics. 158(1). 14104–14104. 10 indexed citations

Wang, Zhi, et al.. (2022). Classical Exchange Polarization: An Anisotropic Variable Polarizability Model. The Journal of Physical Chemistry B. 126(39). 7579–7594. 9 indexed citations

Rackers, Joshua A., et al.. (2022). Predicting accurate ab initio DNA electron densities with equivariant neural networks. Biophysical Journal. 121(20). 3883–3895. 12 indexed citations

Rackers, Joshua A., et al.. (2022). Accurate hellmann-feynman forces with optimized atom-centered gaussian basis sets .. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations

Jing, Zhifeng, Joshua A. Rackers, Lawrence R. Pratt, et al.. (2021). Thermodynamics of ion binding and occupancy in potassium channels. Chemical Science. 12(25). 8920–8930. 33 indexed citations

10.

Koski, Jason, Stan Moore, Raymond C. Clay, et al.. (2021). Water in an External Electric Field: Comparing Charge Distribution Methods Using ReaxFF Simulations. Journal of Chemical Theory and Computation. 18(1). 580–594. 21 indexed citations

11.

Rackers, Joshua A. & Jay W. Ponder. (2019). Classical Pauli repulsion: An anisotropic, atomic multipole model. The Journal of Chemical Physics. 150(8). 84104–84104. 70 indexed citations

12.

Rackers, Joshua A., Chengwen Liu, Pengyu Ren, & Jay W. Ponder. (2018). A physically grounded damped dispersion model with particle mesh Ewald summation. The Journal of Chemical Physics. 149(8). 84115–84115. 18 indexed citations

13.

Rackers, Joshua A., Zhi Wang, Chao Lü, et al.. (2018). Tinker 8: Software Tools for Molecular Design. Journal of Chemical Theory and Computation. 14(10). 5273–5289. 488 indexed citations breakdown →

14.

Lagardère, Louis, Nohad Gresh, Qiantao Wang, et al.. (2016). Scalable improvement of SPME multipolar electrostatics in anisotropic polarizable molecular mechanics using a general short‐range penetration correction up to quadrupoles. Journal of Computational Chemistry. 37(5). 494–506. 23 indexed citations

15.

Rackers, Joshua A., Qiantao Wang, Chengwen Liu, et al.. (2016). An optimized charge penetration model for use with the AMOEBA force field. Physical Chemistry Chemical Physics. 19(1). 276–291. 72 indexed citations

16.

Wang, Qiantao, Joshua A. Rackers, Chenfeng He, et al.. (2015). General Model for Treating Short-Range Electrostatic Penetration in a Molecular Mechanics Force Field. Journal of Chemical Theory and Computation. 11(6). 2609–2618. 93 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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